BBDO Proximity: Big-data May 2013


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BBDO Proximity: Big-data May 2013

  2. 2. 22WhyBigData?Organizations are facing bigger and bigger challenges when itcomes to collecting and using data. Companies can access largeamounts of information, but do not know how to interpret it toobtain results that provide added value for their businesses orcustomers. Often this is due to the raw availability of the data andits lack of structure, or the lack of the technological infrastructureand knowledge needed to make use of it. But all of this ischanging, thanks to what has come to be known as “Big Data.”
  3. 3. 3The best way to start the conversationabout “Big Data” is to define it. Its name isperhaps confusing and not quite apt, sinceit implies that existing data is “small,” orthat we simply have a lot more data. Thereality is, the term Big Data is applied toinformation that cannot be analyzed withtraditional tools or processes.Big Data has three fundamentalcharacteristics: it involves managing alarge volume of information, processingthe data quickly or in real time, andintegrating a large variety of informationsources that may be able to drawconclusions from data connections thatare not apparent from the start.
  4. 4. 4A recent study discovered that a largeamount of today’s business leaders areaware that they do not have accessto all of the insights that would helpthem improve decision-making in theircompanies. The companies, in turn, arefacing increasing challenges in a timein which data is being generated likenever before and in which they have thecapacity to store this information. Thisrepresents a great opportunity for thesecompanies to equip themselves with real-time knowledge that can truly help themunderstand and adapt to individualsand their needs, and make decisionsaccordingly.It may seem paradoxical, but while itis possible for today’s businesses toaccess information that can potentiallybe decisive for their core strategies, theircapacity to process, filter and analyzeincreasing quantities of information isdecreasing. The data – which couldrepresent a truly golden opportunity –just continues to pile up. This is whereBig Data comes in as a key player for thebusiness.1
  6. 6. 6$5 billion in Big Data software, hardware,and services$50 billion estimated for 2017$1.1 billion revenue for IBM comes fromBig Data70% of data storage is in North Americaand Europe60% potential increase in the operatingmargin for the retail sector$10 billion potential health-related marketfor Big Data in 2020180,000 Big Data experts will be neededover the next 5 years in the USA2,470 venture capital fund investments inBig Data companies in the USA in 20111 billion gigabytes of data on the Internet40% annual growth worldwideBig Datain Figures2012 MARKETGROWTH FORECASTSLEADING COMPANYGEOGRAPHYRETAILERSHEALTHDEMAND FOR LABORINVESTMENT FINDSINTERNET DATADATA GENERATION
  7. 7. 7The world is changing in leaps andbounds. We use more and moretechnological devices in our daily lives,and thus we are able to capture morethings. It has been observed that whenwe can capture things, we tend to holdon to them.Thanks to technological progress,people and objects are increasinglyinterconnected 24 hours a day without anytype of interruption. This interconnectionis rapidly escalating, and the flow ofdata exchange that it inspires is growingwithout bounds. The reduction in thesize and price of circuits, like those usedin smartphones, watches, heart ratemonitors, mp3 players, and tablets, etc.,contributes to this growth. Thanks to thedecreased cost of these circuits, we arenow able to endow just about everythingwith “intelligence”–even a floor cleaner likethe Roomba–and obtain answers from this“intelligence” in the form of data.These types of devices are highlyreliable, sufficiently enough to have beenimplemented in security systems forsome time now. For example, a freighttrain has hundreds of sensors thatmonitor the climate conditions insidethe wagon, the status of certain piecesof machinery, or shipments. Theseprocessors interpret in real time the datafrom sensors in parts that are proneto wear, like the bearings, in order toidentify the components that are inneed of repair before they fail andpotentially cause a problem. The railsalso have sensors.
  8. 8. 8This data implies a fundamental changein the way we analyze this data, sinceit no longer follows a traditionalstructure and therefore requiresmore sophisticated technologies andmethodologies.The success of an organization willincreasingly stem from and dependon its ability to draw conclusionsregarding the diverse types of dataavailable to it. Getting ahead of thecompetition requires, in the majority ofcases, identifying a trend, a problem,or an opportunity microseconds beforeanybody else. That’s why organizationsmust be able to analyze this informationif they want to gain insights andknowledge that will help them with theirbusiness. They must start by identifyingthe opportunities behind Big Data, as thispaper seeks to illustrate.
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  10. 10. How much datadoes socialmedia generate?10More than 144.8 million emails sent/received per dayMore than 684,000 pieces of content and 34,000 brand “likes”More than 340 million tweets per dayMore than 72 hours (259,200 seconds) of video consumedevery minute272,000 dollars transacted every day
  11. 11. 113,600 new photos every minuteMore than 2 million queries every minute3,125 new photos every minuteAround 47,000 application downloads per minuteMore than 2,000 check-ins every minute27,000 new posts every minute571 web pages published every minute350 new entries every minute
  12. 12. 1212AccessibilityandTechnologyare KeyBig Data was one of the main subjects discussedat the Oracle OpenWorld 2011 conference. Thefocus on Big Data at this conference revolvedaround offering enormous machines with massivecapacities, multi-parallel processing, unlimitedvisual analysis, and treatment of heterogeneousdata, etc. In short, solutions designed to meet theregular, massive needs of large organizations.
  13. 13. 13However, other types of companies optfor approximations using cloud-basedand open-source tools, like Hadoop, apopular open-source software frameworkthat allows applications to work with largeamounts of data and thousands of nodes.Hadoop was inspired by tools used byGoogle and by non-relational databasesnecessary for storing and processingthe enormous complexity of all typesof data, which in many cases do notfollow the logic of ACID (Atomicity,Consistency, Isolation and Durability)guarantees, typical of conventionaldatabases. It seems that solutions of thistype will be increasingly adopted in thefuture, although exciting questions abouttheir implementation and uses remainunanswered.
  14. 14. 14It was precisely with the idea of increasingBig Data’s reach that Google introducedBigQuery some time ago, an onlineservice for processing large volumesof information. The service, however,is targeted towards professionals, andtherefore it is not free of charge.With BigQuery, Google takes advantageof all its knowledge on processing largevolumes of information and making itavailable to companies that are unableto purchase their own infrastructure, thusoffering them a cloud-based modelthat provides storage space as wellas a data-mining service. Thanks toBigQuery, companies can make theirfirst inroads into processing largevolumes of information, although,logically, it may be necessary to hire aspecialized service in order to receivemore in-depth service or analysis. Evenso, Google’s initiative seems to be ofinterest, as it is a way to advertise BigData around the world.
  15. 15. 15In any case, the utilities and applicationsthat Big Data can provide are alreadywithin reach for many users, and in away that allows them to recognize andunderstand the massive convergence ofdata. Any user may consult and use thetools that already exist on the Web.For example, a user may go to GoogleMaps, write an address, choose thesatellite view, and see the traffic in thearea that he/she wants to visit in real time,based on information that other usershave sent to the network via an Androidterminal. Google has also discovered thatcertain search terms are valid indicators ofthe evolution of the flu, and the resultsare shown on Google Flu Trends.2Approximate calculations of flu activitycan thus be made for certain regions,which could be of use when it comesto taking preventive action. We can findother similar examples to the one justmentioned.2
  16. 16. 16Another facet of Big Data that has a strongpotential for further development involvescitizen access to public data, which, untilnow, was only available for analysis bythe public administrations. In 2009, thegovernment of the United States was apioneer by opening the doors to all of itsinformation on the website, you can access a great dealof information that has been available toUS residents for a while now. To date,the site has received more than 100million visits, and local authorities andinstitutions have started to release theirdata to citizens, following PresidentObama’s lead. Cities like San Franciscoand New York, and the states of California,Utah and Michigan, among others, havelaunched their own websites based on model. The same is taking placein countries like Canada, Australia andthe United Kingdom, and with such well-known institutions as the World Bank.Another public-interest use for Big Datawas developed by IBM.3Using “SmartMeters,” IBM analyzed a neighborhood’spower consumption with sensorsthat provided energy consumptiondata, with the goal of making thatconsumption more efficient. Based onthis information, the company was ableto determine inhabitants’ energy-usagepatterns throughout the day, see howdemand varied, and even change someof those patterns by implementingvarious strategies and client discounts.3
  17. 17. 17The benefits of intelligent analysisThe insights detected by Smarter Analytics help companies make faster and better decisions and automateprocesses. In addition, they contribute towards building a solid foundation of product analysis and strategicservices in order to take advantage of all data sources, both structured and unstructured. All this data willalso support taking decisions at times of change and help companies move beyond the competition.Increase data oncustomers and retainthe most valuable onesContinuallyimprove operationalefficiencyPrevent fraudandmanage riskTransform andautomate financialprocesses
  18. 18. 18Even the Leicester Tigers rugby team hasstarted using Big Data to help preventinjuries.4Thanks to the increasing availability ofpublic data, people have developedhundreds of applications that society canbenefit from, for example, applicationsthat allow you to see pollution levels byregion, that help travelers find the fastestroute to their destinations, and that informnew homeowners about the safety oftheir neighborhood. Never before has somuch valuable, objective information beenavailable to help people make the bestdecisions possible in their day-to-day lives.As opposed to the way things usually findpopularity, Big Data is being propelled bythe public sector, as it shows people itsvalue and potential. The time has comefor Big Data to expand into the privatesector, and for marketing and customer-relations departments to take advantageof the opportunity to increase their profitsand productivity, and to be able to adapttheir business strategies to the newchanges that are to come by using all theinformation available through Big Data.4
  19. 19. 19191 in every 4rugby players isinjured duringtraining sessionsHamstring injuriescause players tohave to sit outan average of14 gamesResearchers areusing equationsto predict sportsinjuriesThe organizationsthat apply predictiveanalysis are 2.2times more likely tobeat their opponentsUsing data to stand up to rugby injuries
  20. 20. 2020MarketingwithBig DataDigital is the new frontier. Everything is goingdigital. As a result, people, devices andcompanies are managing larger and largeramounts of data. Companies need to find a wayto innovate in terms of examining all this data, soas to create actions and concrete strategies thatwill add much more value.
  21. 21. 21“One of the biggest changes we’re seeingin the online advertising industry is anincreased focus on data and analysis.Marketers are hungry for information aboutwhat their audiences do online and howthey’re responding to ads. At the sametime, it’s not always easy to navigate withmassive amounts of data, so, in order tobe meaningful, that data needs to becombined with insights so marketersunderstand how to activate on thefindings.”–Lauren Weinberg, VP, Strategic Insightsand Research, Yahoo!
  22. 22. 22Large companies are aware of this andare increasingly dedicating departmentsand resources to data collection andapplication.
  24. 24. 24Big Dataand CRMThe large quantity of information beinguploaded to the Internet representsa wonderful opportunity to segmentaccording to people’s behavior andnot just by socio-demographic factors.Companies acquire transactionalinformation from their customers bymaking them fill out forms, but thechallenge for brands is to enrich theirdatabases with information on thecustomers’ daily habits and behavior,which can be obtained from online chatsand then processed, crossed and enrichedwith many other types of informationthanks to Big Data-based initiatives.This way, we can build databases ofinformation available on customerswithout needing to bother them againand again, and then we can use thisinformation to offer proposals with ahigher added value.Take, for example, something simplelike the opportunities for personalizingpromotions. Let’s imagine that we couldknow that the customer is a member ofan online wine community, which clearlyindicates that he is a wine aficionadoand not just someone of the “I like wine,but I like beer, too” type. Through adigital customer loyalty card—like thePassbook application on the new iPhone5—we could keep a record of all of hiswine purchases, and even get an ideaof what wine he orders in restaurants.Could an online supermarket thenpersonalize its newsletter for him withwines similar to the ones he likes? Tryto sell him a bottle of wine that he hadtried the night before in a restaurant?Or, imagine another case: a customerstarts to access an online real-estateportal more and more often. Couldhis bank or a competing bank be ableto offer him options from among theirhousing in stock before he asked forthem? Perhaps someone tweets thathe is renting an apartment. Wouldn’tthis information be of interest to thecompanies that offer home insurance?If Google’s contextual advertising isalready working along these lines, whynot improve our own CRM systems inthe same way?
  25. 25. 25Using the same technology with thecorrect platform and the appropriatetactics, we can achieve more ambitiousobjectives and provide very valuableinformation for brands, which can then usethis information to enrich their customers’experience. All we need are technical andhuman systems that are able to collect,standardize and mine the information.The implications for customer-servicestrategies are also significant.Big Data has recently gained relevancebecause companies are realizing what itcan do for them, and that it is a goldminefor finding competitive advantages. Whenit is applied to the realm of business ormarketing, the whole conversation aboutBig Data revolves around consumertrends, developing new products, andother insights into the market. WhenMcKinsey wrote its report on Big Data5last year, it identified five different waysin which Big Data can be used to createvalue, but only one of them mentionedcustomers, and it did so in order todiscuss improvements in consumersegmentation. The Wall Street Journaldescribes several successful storiesfrom different brands in its blog on BigData,6but focuses almost exclusivelyon operational issues, processmanagement, and other efficiency-improving aspects. Efficiency is clearlya goal worth pursuing, but the use ofBig Data is much more relevant in therealm of content or customer service.Now that consumers have seen whatsocial media and mass personalizationare capable of, they increasingly expecttheir favorite brands to provide theseengagement opportunities. They are notmerely passive users waiting to receive amessage. Rather, they want to be activeparticipants.Customer experience designers areaware of this. When a customer callsthe customer service number, sends anemail, or speaks with an employee in astore, they are starting a conversation.At that moment, the brand holds all ofthe customer’s attention, even if he orshe is annoyed, which means that thebrand has been given an importantopportunity to define its relationshipwith its users. The user knows that thebrand has gathered information aboutits customers for its own needs, and hein turn will ask why doesn’t the brand doanything useful—for the customer, notjust the brand—with this data.5
  26. 26. 26Listening to online conversations may helpcompanies provide better services andintegrate social channels with customer-service channels, thus hugely improvingthe user experience. Technically, thiscan be very difficult to achieve, butAmazon does it particularly well. Amazonhas grown quite a lot over the years,but it has always stayed constant as aunique organization. Other organizations,however, have become larger by wayof acquisitions, which make datasynchronization an extremely technicallycomplex task, with a high demand forresources and investments.Even so, if the new pattern ofrelationships between brands andconsumers is here to stay, companiesmust invest in capturing, processing andsynchronizing data between channelsand platforms, which is somethingunique to human interactions. If you talkto a friend, for example, and constantlyask him for information that you alreadyhave, he would understandably getannoyed. In the era of Big Data, thesame rules apply to brands. The onesthat follow the rules will win the trust andloyalty of their customers.
  27. 27. 27  Are you a new customer? Start here.
  28. 28. Sean’sexperience withAmazon28Sean Madden is a consultant who haspurchased many items on Amazon forover a decade. One day he contactedthe online customer service becausehis Kindle was not working properly.Thirty seconds after he reported theproblem, Amazon called him on thetelephone. The employee on the otherend of the line greeted him by his firstname and fixed the problem in less thantwo minutes. Sean never had to providehis product information, registrationnumber, or other details of the problem.Sean writes in his blog that hedidn’t expect anything clear tocome out of that call, let alone thatAmazon would fix the issue. Likemost of us who have experiencewith these types of calls, weare accustomed to hearing acold, scripted, robotic voice, thetone of which depends on howsympathetic the operator feelsthat day.
  29. 29. 29But, on the contrary, Sean’s experiencewith Amazon was positive and fluid.Amazon surprised Sean by using his dataand purchasing-history profile to providehim with a fast and personal repairservice, as well as personalized advice,based on his customer history profile.The fact is that Amazon had beencollecting information on Sean for years,not just his different addresses andpayment information. They created anidentity of Sean “as a person” and theyused it to build a two-way relationshipwith him.With what CRM is traditionallyable to offer, combined with socialdata, that is processed extremelyquickly, and used to obtainmassive knowledge of all of thecustomers as a whole, Big Databecomes truly powerful.
  30. 30. 30One of the main ways that brandscan generate interesting content fortheir targets using Big Data involvesself-quantification.Self-quantification is not new. Peoplehave always meticulously measuredmany aspects of their lives, whether bypainting or drawing, recording wherethey are, when and what they eat, or howthey feel. Journals and, in today’s world,blogs are examples of this. But onlyrecently have technological advancementsfacilitated a real explosion of these typesof activities. An ecosystem of content andapplications is developing on the basisof an increasingly transparent and socialculture with the ubiquitous presence ofsophisticated devices and sensors thatmake it possible to record and monitoractivities, such as the GPS, cameras,microphones, accelerometers, etc. Thisecosystem is based on monitoring ouractivities with systems that are less andless declarative and more and moreobjective.Smartphones are the most comfortable,convenient, and omnipresent technologyfor the growth of this ecosystem.Worldwide sales of smartphones grow ata pace of 50% annually, and for 89% ofusers,7these phones have become theirconstant companions throughout theday. Never before has it been so easy forpeople to collect and store their own data.Big Data providesnew contentfor consumers7 The Mobile Movement study, by Google / IPSOS (April 2011).
  32. 32. 32General Electric, in conjunctionwith the online medical communityMedHelp, has launched fourapplications for the iPhone that tracksleep, weight, pregnancy, and stateof mind. As the users implement thesetools in order to monitor their owndevelopment, MedHelp collects allof the data.GeneralElectric
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  34. 34. 34Nike is another brand that chargedheadfirst into the year with a new product/service that expands the possibilitiesof its successful ecosystem Nike+: theNike FuelBand. This system allows usersto track their daily activity and see theirprogress.Nike+ FuelBand has an LED screen whereyou can see the information gatheredabout the activities in your day, sensedand collected via wrist movements. Theuser sets a goal for how active he/shewants to be during the day and his/hermovements are recorded and measuredby the bracelet with 20 LED lights, whichchange from red to green as the usernears his/her goal. There’s a websitewhere all of your NikeFuel points areaccumulated, so you can compare yourperformance based on the time, day,week, month, or year using differenttypes of graphics. You can also compareyour data to that of your friends in theNike+ community. This device can alsobe synchronized with the iPhone andthe data can be viewed using a freeapplication.NikeFuelbandAlthough similar devices like Fitbitand Jawbone UP have existed since2009, Nike waited for the trend to gomainstream, in order to execute a majorlaunch that would position the brandas the leader of its category and as thereference brand for this type of gadget—in short, becoming the company thatdemocratized the measurement ofsports performance and well-being forall users. Ultimately, Nike has been atrue game-changer, offering relevantservices to its consumers thanks todata mining. If all of this informationis analyzed on a large scale, theopportunities for the brand are infinite.“Nike is becoming a company thatisn’t just focused on products, but onproducts and services. It used to bethat when you bought a product, thatwas the end of the relationship. It’sclassic marketing. Great, you boughtthe product. See you in a year, whenthe next campaign comes along. Thatthinking has flipped on its head. Now,the purchase of any Nike product needsto be the beginning of the relationshipwe have with the consumer.”–Stefan Olander, VP Digital Sport
  35. 35. 35  The system allows users to track their dailyexercise and see their progress. As the claim states,“Make it count.”
  36. 36. 36The real estate website Trulia (New Yorkhousing sales and rentals), has launchedan interactive “commute map” thatallows users to view their route to workin a dynamic format. This is especiallyuseful for those who plan to move to anew neighborhood, since they can easilysee on the heat map how long it will taketo get to work or to other places. Whenusers specify a starting point, the durationof the trip will immediately be shown inreal time on the heat map. Using the slider,users can see the sites they can reachquickly, as well as those that will takelonger. Trulia helps its potential customersmake better decisions, and positionstheir site as a more useful space, thusgenerating traffic and sales. The commutemap is a useful tool for communicatinga large quantity of information in aneasy-to-understand format. It uses thetraffic information and the OpenStreetMapdata to create a visual image with arange of colors that represent the differenttravel times.Trulia
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  38. 38. 38The Eatery is an application developed byMassive Help (USA), which lets users takepictures of their food and rate other users’food photos based on their perception ofwhether or not what they see is healthy.Since its launch last year, this platformhas acquired a vast quantity of data fromhundreds of thousands of users. MassiveHealth has used the photo ratings toanalyze how our friends influence whatwe eat. If you are obese and you have apartner, there is a 34.5% chance that heor she is also predisposed to obesity.This percentage increases to 57% whenit’s your friends who have weight issues.With this information, Massive Healthhopes to help people improve their foodhabits. They’ve found out that peoplewho eat healthier food tend to sticktogether, and therefore the applicationseeks to facilitate contact between peoplewith healthy and not-so-healthy habitsin order to promote better attention tofood choices.The Eatery
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  40. 40. 40Walmart gained Big Data experiencewith its purchase of Kosmix in April of2011, with which it created WalmartLabs.Kosmix’s expertise was in analyzingenormous sequences of data from socialnetworks in order to help companiesunderstand what consumers are sayingabout products and brands. Wal-Mart isalso trying to use social network trendsto influence the marketing and inventorydecisions on their website and in theirstores. Their technology, called SocialGenome, uses the aforementionedHadoop and other open-source tools tocapture and analyze in real time the flowof comments made on Facebook, Twitter,and other social networks that revealwhat people think about certain products,brands, places, and events. Walmart haseven developed its own technology torapidly analyze the data.WalmartLabs’ first innovation with thistechnology was Shopycat, launchedin December of 2011. Shopycat is anapplication that recommends gifts tofriends and family members based onyour tastes and likes on Facebook. ItsWal-Martobjective is to turn insights aboutthe consumer, extracted from socialnetworks, into practical shoppingadvice. Shopycat is capable ofinterpreting unstructured data like thefeelings behind a Facebook statusupdate, which are difficult for traditionaldatabases to analyze. Shopycat alsoidentifies which items are “better gifts”than others, using an algorithm thatanalyzes multiple aspects such as howrecently the product was launched, itsuniqueness, and the user’s purchasingbehavior on Walmart istaking an unconventional approach tooffering gift recommendations. If thecompany does not find the best productin line with a recommendation onlineor in a local store, it will send theuser to another retailer who does havethat product.
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  42. 42. Privacy42As the relationship between marketingand Big Data evolves, brands needto examine how to obtain informationwhile not only protecting the privacyof their customers or users, but alsodemonstrating that they are making theeffort to do so.In a world where we increasinglycapture more and more information,and where information comesfrom the daily use of all types ofdevices, we have to be ever moreresponsible about the use of data.What’s more, consumers and usersare also becoming more aware. Theyare informed about how companiesuse information and they demandsuitable data protection policies thatare perhaps not always compatiblewith maximizing marketingopportunities, even when thoseopportunities would benefitthe users.In this context, the public responseis unpredictable and variable.BlackBerry has been severelycriticized in public for leakingcertain data, and Twitter has beenpraised for protecting it. Googlebecame the center of attentionwhen The Wall Street Journalrevealed that the US governmenthad obtained a secret court orderto force Google and the Internetservice provider togive up all of the email accountinformation of the famous hackerand WikiLeaks volunteer, Jacob
  43. 43. 43Appelbaum, who had not been accusedof a single crime. The Wall Street Journaldisclosed how the ISP secretly foughtto avoid providing the information until itwas forced to do so. Google, in turn, didnot comment on the WSJ exclusive, thuscreating discontent amongst online users.These types of cases generate a greatdeal of controversy.On the other hand, we often lose sightof the idea that certain data is personaland must be protected. For example, theRitz-Carlton chain has taken big stepsforward in the hotel industry, improvingits hospitality by collecting a lot of datafrom its customers, with the sole goal ofimproving customer service.For now, this seems valid and noone has complained. That said,it can also be counterproductivefor a service to become “toogood” as a result of data analysis:the customer who notices howproposals or content are alwayspersonalized may feel “watched”or frightened about the company’sdata-gathering methods.Balance appears to lie in acombination of strictdata-protection policies thatallow information to be used toimprove services, but are alwaystransparent with regard to whatinformation is being used and why.
  44. 44. 44The marketing benefits of Big Data are notjust related to the possibility of offeringimproved content or better applicationsfor consumers. Rather, Big Data can alsobe used to improve the products andservices offered by brands, or to facilitatemarketing decision-making beyondconventional market research.Wal-Mart itself has had positiveexperiences with this. This is because itsefforts to make the most of opportunitiesthat lie within data analysis wentbeyond just personalized productrecommendations. An example of thiswas when Walmart detected an increasein demand for juicers which correlatedwith the premiere of a Netflix movie thatexamined the health benefits of juices. Asa result, the company promoted its juiceswith this theme.Big Data canimprovedecision-makingand promoteinnovation
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  46. 46. 46Netflix, a company that streams televisionseries and movies online, recentlypurchased the license for a televisionseries, surpassing the bid proposed bythe cable TV channels HBO and AMC,in order to guarantee their rights to theseries House of Cards. This is the firsttime that Netflix has invested in originalcontent. Netflix, since its founding, hasdistributed television content using asubscription model (physical shipmentof DVDs through the mail), and now hasbroadened its business to provideon-demand video streaming. The contentis transmitted online to consoles like theXbox 360, Nintendo Wii, the PS3, andother devices like Blu-ray players andSmart TVs connected to the Internet, inaddition to smartphones, tablets andcomputers.The series the company purchased is aremake of a BBC political thriller. It willbe directed by David Fincher and will starKevin Spacey. What Netflix did was collectlarge quantities of data from all of itssubscribers in order to determine if theywould want to watch this combinationNetflixof political thriller, director, and actors.The answer was yes. And not just that,but the same data that helped Netflixdecide which series to purchase willnow help the company promote iteffectively among their subscribersthrough their recommendation system,which suggests 75% of what users endup watching, according to the company.To understand the context, it helps tokeep in mind that in the month of June,Netflix streamed more than one billionhours of online video to its subscribers.Well-managed data collected on itsviewers can help the company finda new series in the future or moviesthat will be in line with what Netflixcustomers want to watch.
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  48. 48. 48Another interesting case is that of thestartup Bluefin from the MIT Media Lab.Bluefin associates the conversations heldon social networks with television in orderto help brands. This allows producers,television channels and brands to seewhich content generates the most interestand connections among the viewers,which is an interesting step forwardin measuring audience sentiment andengagement.Founded by professors Deb Roy andMichael Fleischman in 2008, Bluefin scansmore than three billion mentions on socialnetworks per month and crosses themwith an archive of “visual signatures” ofmore than 200,000 television programsfrom more than 50 channels. This data isused to provide retrospective informationMITMedia Labon what viewers were saying about theprogram when it aired.This can help brands reach a higherlevel of understanding, with a deeperand more precise grasp of howviewers see the program and itsadvertising. It allows them to check howadvertisements work in different timeintervals, and on different channels orprograms, as well as how they stand upto their competitors.
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  50. 50. 506 Key Points50BIG DATA IS ALSO FOR MARKETING:The term Big Data refers to infrastructures and systems so broad and powerfulthat they can seem unrelated to marketing. But Big Data in fact represents a realopportunity to develop strategies, campaigns, customer experience models, andCRM based on access to and use of never-before-seen levels of data, even whenit doesn’t quite reach the volume truly required.BIG DATA IS A MEANS, NOT AN END:Like any procedure for obtaining knowledge, Big Data is an instrument in thehands of marketers, which can have powerful implications for their businesses,but it should not be a claim or goal in itself.REQUIRES A CROSSCUTTING APPROACH:Big Data involves the capacity to extract and transform data in a powerful waythat would not necessarily be possible with conventional methods. This requiresa cross-cutting approach to integrate data-capturing devices, systems, differenttypes of data, and, above all, an open-minded way of thinking to discover newopportunities.
  51. 51. 5151VALUE FOR CONSUMERS:Strategies based on Big Data have proven to be capable of creating value forconsumers in many fields by helping to develop new tools, applications andproducts that benefit the consumer, while always defending and protectingconsumer privacy.VALUE FOR BRANDS:The ability to connect enormous amounts of data from diverse sourcesconstitutes, at a minimum, a powerful tool for researching nonmanipulatedmarkets. Big Data represents an opportunity for brands to better understand theirconsumers, even providing answers to questions that consumers may not evenbe asking yet. Big Data is also a tool that can have profound effects on loyaltyprograms and CRM customer-service strategies, creating ever more accurate andrelevant personalized communications.BIG DATA HAS IMPLICATIONS:With Big Data, infrastructure, resource, and work-style needs are not trivial, butthey are not unrealistic either. The application of Big Data to marketing is aproposal for the long term.
  52. 52. 52Big Data is starting to enter inaccessiblerealms. It is always possible to collectmore and more pieces of data and askourselves ever more complex questions.The European Organization for NuclearResearch’s Large Hadron Collider atomsmasher generates so much data thatmost of it is ignored and deleted, in theconfidence that nothing of importanceis being discarded—unlike, for example,in the healthcare world, where clinicalhistories, or all of the medical images,such as X-rays and MRIs, could beimportant. There will always be a doctorwho wants to cross-reference data from,for example, all of the X-rays of tumorpatients still alive after five years, whohave families and no alcohol drinking intheir background. Or perhaps we mightwant to analyze power-consumption dataAn emergingissuefrom all power meters to the minute, inorder to make appropriate consumptiondecisions. Why not have meters inevery outlet and in every appliance tocustomize electricity charges as muchas possible? Or perhaps someone mightwant to collect all of the tweets thatmention a specific subject and correlatethem with news items; or follow themovement of every vehicle on theroad; or study the influence of rumorspropagated on social media about stockexchanges and financial products, orabout recently premiered movies or newproducts. And what about a systemthat links a buyer’s personal data fromhis NFC-enabled payment device (NFCis soon to be implemented in cellularphones) with every item purchasedin the supermarket, through the NFC
  53. 53. target incorporated into each productunit? This will soon revolutionize theway we pay for our groceries. The list ofquestions that industries, sectors andcompanies can ask themselves is neverending. So is the list of answers, althoughthe majority of them start from a sharedpremise: concern for the consumer and apush to unveil all the hidden potential ofthis knowledge.In order to apply marketing strategiesbased on Big Data principles, first wemust invest in infrastructure, and systems,and resources with which to analyze allthe data in the spirit of a search that doesnot rule out deep connections betweendata and events that on the surface seemcompletely unrelated. And of course, wemust have the will and the resources to53activate that knowledge in specificstrategies and actions, whether it bethe launch of a new product or thecreation of a cell-phone application thatdistributes new brand content in a newor more effective way.The reward, in the form of value addedfor the consumers and growth andloyalty for the brands, is waiting for you.It is Big Data.
  54. 54. 54El Blog de Enrique DansALT1040The Wall Street JournalPublic TechnologyHarvard Business ReviewFast CompanyVentureBeatlnformation ManagementStatista eMarketer Forrester GartnerSourcesZDNetRobert Kirkpatrick: How TheUnited Nations ls Using SocialData To Spot DisastersTED talk: Kevin Slavin: Howalgorithms shape our worldMcKinsey & Co.TheNextWebThe GuardianForbesBusiness lnsider
  55. 55. 5555About the AuthorsThis document was written by JuanManuel Ramírez, Director of Strategyand Development, and Daniel Camprubí,Planner, at Proximity.Proximity is a digital agency that offersintegrated marketing and advertisingsolutions. By bringing together knowledge,creativity, and technology, we developinnovative ideas and measures able tosolve business @cpproximity